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Simplified Building Thermal Model Used for Optimal Control of Radiant Cooling System

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  • Lei He
  • Bo Lei
  • Haiquan Bi
  • Tao Yu

Abstract

MPC has the ability to optimize the system operation parameters for energy conservation. Recently, it has been used in HVAC systems for saving energy, but there are very few applications in radiant cooling systems. To implement MPC in buildings with radiant terminals, the predictions of cooling load and thermal environment are indispensable. In this paper, a simplified thermal model is proposed for predicting cooling load and thermal environment in buildings with radiant floor. In this thermal model, the black-box model is introduced to derive the incident solar radiation, while the genetic algorithm is utilized to identify the parameters of the thermal model. In order to further validate this simplified thermal model, simulated results from TRNSYS are compared with those from this model and the deviation is evaluated based on coefficient of variation of root mean square (CV). The results show that the simplified model can predict the operative temperature with a CV lower than 1% and predict cooling loads with a CV lower than 10%. For the purpose of supervisory control in HVAC systems, this simplified RC thermal model has an acceptable accuracy and can be used for further MPC in buildings with radiation terminals.

Suggested Citation

  • Lei He & Bo Lei & Haiquan Bi & Tao Yu, 2016. "Simplified Building Thermal Model Used for Optimal Control of Radiant Cooling System," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-15, February.
  • Handle: RePEc:hin:jnlmpe:2976731
    DOI: 10.1155/2016/2976731
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    Cited by:

    1. Hu, Guoqing & You, Fengqi, 2022. "Renewable energy-powered semi-closed greenhouse for sustainable crop production using model predictive control and machine learning for energy management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).

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